Mathematics and Computer Sciencehttp://hdl.handle.net/2092/194
Publications and research submitted by the faculty members of the Department of Mathematics and Computer Science.

2016-12-09T15:24:16ZLIPS: Learning based indoor positioning system using mobile phone-based sensorshttp://hdl.handle.net/2092/2118
LIPS: Learning based indoor positioning system using mobile phone-based sensors
Mascharka, David; Manley, Eric
In this paper we investigate the problem of localizing a mobile device based on readings from its sensors utilizing machine learning methodologies. We consider a real world environment, collect a dense set of 3110 datapoints, and examine the performance of a substantial number of machine learning algorithms. We found algorithms that have a mean error as accurate as 0.76 meters, outperforming other indoor localization systems. We also propose a hybrid instance-based approach that results in a speed increase by a factor of ten with no loss of accuracy in a live deployment over standard instance based methods. Further, we determine how less dense datasets affect accuracy, important for use in real-world environments. Finally, we demonstrate that these approaches are appropriate for real-world deployment by evaluating their performance in an online, in-motion experiment. The Learning Based Indoor Positioning System (LIPS) Android application source has been made available on the web.
2016-01-01T00:00:00ZVideo-Based Instruction For Introductory Computer Programminghttp://hdl.handle.net/2092/2063
Video-Based Instruction For Introductory Computer Programming
Manley, Eric D.; Urness, Timothy
Video replacement of in-­person lecture is finding its way into more and more computer science education settings such as inverted classrooms, massive open online courses, online/distance learning, and programming camps. Since the use of video is critical to some pedagogies, the question of how it impacts student attitudes and learning is important. This study investigates this by looking at experiences in the programming unit within two sections of a broad-­scope CS0 course, one of which used video-­based instruction while the other did not. We found that students in the video section had a more positive view of the learning activities and thought their student-­instructor interactions were more meaningful. Student performance data also suggests that video instruction may benefit student learning as well.
2014-05-01T00:00:00ZMulticast Network Coded Flow In Grid Graphshttp://hdl.handle.net/2092/2062
Multicast Network Coded Flow In Grid Graphs
Manley, Eric D.; Gormley, John
Network coding, a relatively new paradigm for transmitting information through communication networks,
allowing intermediate nodes in the network to combine data received on separate incoming channels
before transmitting on outgoing channels. When compared with traditional routing paradigms, network
coding can result in benefits such as higher throughput, fault-tolerance, and security.
In this paper, we focus on studying network coding properties on a specific class of graphs called grid
graphs. Network coding properties are related to well-known Steiner properties in graphs. Specifically,
Steiner properties of grid graphs are studied, because they model VLSI layout design, which makes network
coding properties a natural extension of this investigation.
In particular, we looked at the maximum size of a communication group that is possible in a grid graph,
given a specific desired transmission rate. Letting rk (G) be the maximum fraction of nodes in graph G that
can be included in a network coded multicast group with an integral flow of size k, we prove that r2(G)<1,
r3(G) < 1
2 , and r4(G) < 1
3 . In the first two cases, we construct families of communication groups on grid
graphs which approach these bounds. In the latter case, we present a family of communication groups
approaching a density of 14
.
2014-04-01T00:00:00ZLow Complexity All-Optical Network Coder Architecturehttp://hdl.handle.net/2092/2061
Low Complexity All-Optical Network Coder Architecture
Manley, Eric D.
Network coding, a networking paradigm in which
different pieces of data are coded together at various points along
a transmission, has been proposed for providing a number of
benefits to networks including increased throughput, robustness,
and security. For optical networks, the potential for using
network coding to provide survivability is especially noteworthy
as it may be possible to allow for the ultra-fast recovery time
of dedicated protection schemes with the bandwidth efficiency
of shared protection schemes. However, the need to perform
computations at intermediate nodes along the optical route leads
to the undesirable necessity of either electronically buffering and
processing the data at intermediate nodes or outfitting the network
with complex photonic circuits capable of performing the
computations entirely within the optical domain. In this paper,
we take the latter approach but attempt to mitigate the impact of
the device complexity by proposing a low-complexity, all-optical
network coder architecture. Our design provides easily scalable,
powerful digital network coding capabilities at the optical layer,
and we show that existing network coding algorithms can be
adjusted to accommodate it.
2014-02-01T00:00:00Z